Abstract
It is necessary to incorporate wind and pumped storage plants in classical unit commitment problem due to the increase in use of renewable energy sources. The cost of power generation will be reduced due to inclusion of the renewable energy resources. In this work a Weibull probability density function is used to predict the wind speed. The proposed Unit Commitment (UC) problem includes the factors account for both overestimation and underestimation of available wind power. Pumped storage hydro plants are also included in the scheduling process to balance the uncertainties in the wind power generation. Premature convergence and high computation time are the main drawbacks of the conventional PSO algorithm to solve the optimization problems. In this work a Modified PSO (MPSO) algorithm is proposed to remove the drawbacks of the conventional PSO to solve the proposed stochastic Unit Commitment problem (SUC).
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Ramya, N.M., Ramesh Babu, M., Arunachalam, S. (2015). Stochastic Unit Commitment Problem Incorporating Renewable Energy Power. In: Panigrahi, B., Suganthan, P., Das, S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2014. Lecture Notes in Computer Science(), vol 8947. Springer, Cham. https://doi.org/10.1007/978-3-319-20294-5_59
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DOI: https://doi.org/10.1007/978-3-319-20294-5_59
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